The executive director for UK deposit-taking supervision executed a surveyed more than 200 banks, insurers and financial market infrastructure firms regarding the use of AI for detecting money-laundering with results to be release at the end of the year. In the meantime banks better be on the lookout for biased AI implementations:
‘Are data being used unfairly to exclude individuals or groups, or to promote unjustifiably privileged access for others?’ Proudman said, adding that recent examples of retailers using overly-personalised marketing can seem plain ‘creepy’.
Boards will also need to consider how to allocate individual responsibilities under the Senior Managers Regime, which requires every activity at a bank to come under the direct responsibility of a named official so it is easier for regulators to identify and punish them when things go wrong.
‘You cannot tell a machine to ‘do the right thing’ without somehow first telling it what ‘right’ is – nor can a machine be a whistle-blower of its own learning algorithm,’ Proudman said.
‘As the rate of introduction of AI/ML in financial services looks set to increase, so too does the extent of execution risk that boards will need to oversee and mitigate.’
Overview by Tim Sloane, VP, Payments Innovation at Mercator Advisory Group
